Table 3.
Classification using multi-layer perceptron neural network using python scikit learn: MLP Classifier (solver=‘lbfgs’, alpha=1e-5, hidden_layer_sizes=(5, 2))
| Truth | Malignant | Benign |
| Predict | ||
| All 104 original features: Accuracy = 75% | ||
| Malignant | 31 | 9 |
| Benign | 8 | 20 |
| 89 features with p-value < 0.05: Accuracy = 83.8% | ||
| Malignant | 34 | 6 |
| Benign | 5 | 23 |
| Truth | ENE | Non_ENE |
| Predict | ||
| All 104 original features: Accuracy = 48.7% | ||
| ENE | 14 | 10 |
| Non_ENE | 10 | 5 |
| 6 features with p-value < 0.05: Accuracy = 76.9% | ||
| ENE | 18 | 6 |
| Non_ENE | 3 | 12 |